CCL

Összesen 2 találat.
#/oldal:
Részletezés:
Rendezés:

1.

001-es BibID:BIBFORM086227
Első szerző:Moghadasi, Mohammad (informatikus)
Cím:Cloud Computing Auditing : roadmap and process / Mohammad Moghadasi, Seyed Majid Mousavi, Gábor Fazekas
Dátum:2018
ISSN:2158-107X 2156-5570
Megjegyzések:Cloud Computing is a new form of IT system and infrastructure outsourcing as an alternative to traditional IT Outsourcing (ITO). Hence, migration to cloud computing is rapidly growing among organizations. Adopting this technology brings numerous positive aspects, although imposing different risks and concerns to organization. An organization which officially deputes its cloud computing services to outside (offshore or inshore) providers and implies that it outsources its functions and process of its IT to external BPO services providers. Therefore, customers of cloud must evaluate and manage the IT infrastructure construction and the organization's IT control environment of BPO vendors [25]. Since cloud is an internet-based technology, cloud auditing would be very critical and challengeable in such an environment. This paper focuses on practices related to auditing processes, methods, techniques, standards and frameworks in cloud computing environments.
Tárgyszavak:Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:International Journal of Advanced Computer Science and Applications. - 9 : 12 (2018), p. 467-472. -
További szerzők:Mousavi, Seyedmajid (1982-) (informatika) Fazekas Gábor (1952-) (informatikus, matematikus)
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:

2.

001-es BibID:BIBFORM086226
Első szerző:Moghadasi, Mohammad (informatikus)
Cím:An Automatic Multiple Sclerosis Lesion Segmentation Approach based on Cellular Learning Automata / Moghadasi, Mohammad; Fazekas, Gabor
Dátum:2019
ISSN:2158-107X 2156-5570
Megjegyzések:Multiple Sclerosis (MS) is a demyelinating nerve disease which for an unknown reason assumes that the immune system of the body is affected, and the immune cells begin to destroy the myelin sheath of nerve cells. In Pathology, the areas of the distributed demyelination are called lesions that are pathologic characteristics of the Multiple Sclerosis (MS) disease. In this research, the segmentation of the lesions from one another is studied by using gray scale features and the dimensions of the lesions. The brain Magnetic Resonance Imaging (MRI) images in three planes (T1, T2, PD)1,2,3 containing MS disease lesions have been used. Cellular Learning Automata (CLA) is applied on the MRI images with a novel trial and error approach to set penalty and reward frames for each pixel. The images were analyzed in MATLAB and the results show the MS disease lesions in white and the brain anatomy in red on a black background. The proposed approach can be considered as a supplementary or superior method for other methods such as Graph Cuts (GC), fuzzy c-means, mean-shift, k-Nearest Neighbor (KNN), Support Vector Machines (SVM).
Tárgyszavak:Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:International Journal of Advanced Computer Science and Applications. - 10 : 7 (2019), p. 178-183. -
További szerzők:Fazekas Gábor (1952-) (informatikus, matematikus)
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Rekordok letöltése1